{"as_of":"2026-08-17T17:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d9308b13101dbeba74622a22dda772d4a7ff6e629da2efa4b635ead75cb1ec1b","coverage":[{"denominator":104,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T00:46:41.787955Z","state":"measured"},{"denominator":103,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":103,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:13:43.823878Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-19T09:12:14.898057Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19330","snapshot_observed_at":"2026-08-16T11:13:43.823878Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.16068","last_updated":"2025-04-22T17:47:01Z","snapshot_observed_at":"2026-08-16T11:08:55.568282Z","submitted_at":"2025-04-22T17:47:01Z","title":"High-performance training and inference for deep equivariant interatomic potentials","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T11:13:43.823878Z"},"links":{"cited_paper":"/paper/2412.19330","citing_paper":"/paper/2504.16068"},"observation_digest":"sha256:ef268b49f8b2a7150b9d831f4dfaea40f56d3af302518a3aa1a3103e5b8b119a","observation_id":"ea36cfd2-4faa-499d-8499-61e443e24831","resolution":{"observed_at":"2026-08-16T11:13:43.823878Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"cited_work":{"arxiv_id":"2412.19330","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.19330","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"d4698df2-0f21-45ed-871b-ec59b67de569","year":2025},"citing_paper":{"arxiv_id":"2506.12174","last_updated":"2025-06-13T18:53:42Z","snapshot_observed_at":"2026-07-06T21:42:02.481535Z","submitted_at":"2025-06-13T18:53:42Z","title":"Approximate Excited-State Potential Energy Surfaces for Defects in Solids","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-19T09:07:53.498000Z"},"links":{"cited_paper":"/paper/2412.19330","citing_paper":"/paper/2506.12174"},"observation_digest":"sha256:90e714d81ab6ec7f1e8b154b4b969a670c5a7b27712fc7895f4eab3afc53d7c2","observation_id":"ad94bb5a-d321-4f38-8456-cd27f25e8088","resolution":{"observed_at":"2026-05-19T09:12:14.901227Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"cited_work":{"arxiv_id":"2412.19330","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.19330","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"d4698df2-0f21-45ed-871b-ec59b67de569","year":2025},"citing_paper":{"arxiv_id":"2508.09113","last_updated":"2025-08-12T17:45:31Z","snapshot_observed_at":"2026-08-16T11:10:04.753595Z","submitted_at":"2025-08-12T17:45:31Z","title":"Machine Learning Phonon Spectra for Fast and Accurate Optical Lineshapes of Defects","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-18T22:41:46.289356Z"},"links":{"cited_paper":"/paper/2412.19330","citing_paper":"/paper/2508.09113"},"observation_digest":"sha256:98d297ea1c178f2ef6c94f138d832c17db9d1bffe711a514c3ffe91c4bbc6a32","observation_id":"72678725-2d46-4ae0-94d8-13ca4c2e4c26","resolution":{"observed_at":"2026-05-18T22:41:52.909953Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.19330/citation-record","integrity":"/paper/2412.19330/integrity","json":"/paper/2412.19330/citation-record.json","paper":"/paper/2412.19330"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.248441Z","title":"Freysoldt, B","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.248441Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:427d71840298a6adb7910b2bd66a74b74559daffc29406f811b88c31483a11cc","observation_id":"0df5689a-61ae-4c4a-9bf7-8961429a90a3","resolution":{"observed_at":"2026-08-11T00:46:41.248441Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.254452Z","title":"Mosquera-Lois, S","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.254452Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:bdcccfc1d0f1bdfa0b3ae7406b35b55a9921d76f227a80535502de1246f5bfce","observation_id":"c719f390-151b-4e32-96e5-dc580789ac70","resolution":{"observed_at":"2026-08-11T00:46:41.254452Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.259927Z","title":"Oba and Y","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.259927Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:e918a85121dab053ed9977636a9e654b0f859679eb56aa5587f9ee7a2d82c8ef","observation_id":"bdcc8987-1899-4560-926e-d717e388ab55","resolution":{"observed_at":"2026-08-11T00:46:41.259927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.266758Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.266758Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:d58819d6697cc781dac262400635730840ea830a3d43acc6ea823d0c23bca0c8","observation_id":"6689c8fa-5e88-42db-8be5-0df128b338ce","resolution":{"observed_at":"2026-08-11T00:46:41.266758Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.272068Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.272068Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:a844392dbeb1699faec00c835547e488c5c716121f144b29915fe1db12f1ec2b","observation_id":"df7c5c14-355e-4a0d-9976-649c440f5f8d","resolution":{"observed_at":"2026-08-11T00:46:41.272068Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.277471Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.277471Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:c2cd8d1e2660593fbbe43222c0a5c6d4226279a72a30815232ea08fdc45feff3","observation_id":"e1b73b25-e9f9-4108-8b02-1570ba239b7d","resolution":{"observed_at":"2026-08-11T00:46:41.277471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.284807Z","title":"Zhang and S.-H","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.284807Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:c211af8b09a5996e51cc4f1fdb902f027a150b276f6d3e6ce7de68fcad89e025","observation_id":"4d276e24-ba8d-4212-96e0-6bd59f02bc78","resolution":{"observed_at":"2026-08-11T00:46:41.284807Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.290160Z","title":"Kumagai, S","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.290160Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:ffd4a03aacdc703826c3de9285cee9390a758c7965bc6cc211436e1e1475925a","observation_id":"2932f90a-b260-4653-8d7f-f8499fa5e60b","resolution":{"observed_at":"2026-08-11T00:46:41.290160Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.298483Z","title":"Mosquera-Lois and S","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.298483Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:820582a613a9863654ef077434726dad7a1f949a2506afaa41e733f9a1a8cd91","observation_id":"1eb54f0c-a055-43fd-98a7-862e13f71f0a","resolution":{"observed_at":"2026-08-11T00:46:41.298483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.304211Z","title":"Kononov, C.-W","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.304211Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:cab2103541446e3e85bb71c45e5f6482182974f3b741cfd8e4a1c2065c22ae0f","observation_id":"0ad5df4f-fd60-4421-bd89-7904e911b805","resolution":{"observed_at":"2026-08-11T00:46:41.304211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.310219Z","title":"Mosquera-Lois, S","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.310219Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:9156d3901a4d5a0a9c7d0a87d8994b08cb8909fd8a2bc6056a038143daaffc9a","observation_id":"c627a48a-b15a-4428-a36e-bf76a2719b5a","resolution":{"observed_at":"2026-08-11T00:46:41.310219Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.318041Z","title":null,"venue":null,"work_id":null,"year":1977},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.318041Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:d30d40277706ab9a089c194166c60e7699df3c9a25bb13c86b61041c5b53304d","observation_id":"c172ca3e-c0f2-421b-a129-e7d5e50dffb3","resolution":{"observed_at":"2026-08-11T00:46:41.318041Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.324557Z","title":null,"venue":null,"work_id":null,"year":1989},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.324557Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:42f0f75db8654cc6366b0761457447dd2bba7eb116899eb9ca2031efcded639e","observation_id":"9ca07c87-6fd4-4c9c-999d-3dd9e94d3520","resolution":{"observed_at":"2026-08-11T00:46:41.324557Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.330373Z","title":"Alkauskas, C","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.330373Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:208809a1ba767ad1f913ea9bdfd9c1ee6ea747ba34f6b5c375a00bc88ac854ec","observation_id":"b0ba612e-f997-4fae-b1c5-a21c56b4d456","resolution":{"observed_at":"2026-08-11T00:46:41.330373Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.336215Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.336215Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:77d86562d558f9d9d597230b427715960e6d5f49b2bf02496d096f690370a60e","observation_id":"3d089043-7bed-433d-8672-6d3bace8444f","resolution":{"observed_at":"2026-08-11T00:46:41.336215Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.341727Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.341727Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:7c94e071e82c71f9012dc31e186e27fb901f3c9aa86816a3e1c568748a3751cd","observation_id":"40121d6b-c64e-4453-be75-04a897f09ecf","resolution":{"observed_at":"2026-08-11T00:46:41.341727Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.01733","last_updated":"2023-12-04T08:55:03Z","snapshot_observed_at":"2026-08-16T14:37:56.794986Z","submitted_at":"2023-12-04T08:55:03Z","title":"Metastability and anharmonicity enhance defect-assisted nonradiative recombination in low-symmetry semiconductors","version":1},"cited_work":{"arxiv_id":"2312.01733","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.01733","snapshot_observed_at":"2026-08-11T00:46:41.988433Z","title":"Metastability and anharmonicity enhance defect-assisted nonradiative recombination in low-symmetry semiconductors","venue":"cond-mat.mtrl-sci","work_id":"64ce3f21-0d76-4411-95bc-0a5dc1f1fd52","year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.347428Z"},"links":{"cited_paper":"/paper/2312.01733","citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:89a599602a2b9c902c51cb8968b3d3c2c960d9f3ebbe0619a33e9fcf48e808fa","observation_id":"5b5aef1f-b195-48a3-9b07-376439bbfc30","resolution":{"observed_at":"2026-08-11T00:46:41.994355Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.354828Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.354828Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:3726a75011b417ad7f2419c80454208afb3bff2ce5ed3c9d7e5001421a664bee","observation_id":"e7a14c4e-633a-4e15-bc75-157c4fc904ca","resolution":{"observed_at":"2026-08-11T00:46:41.354828Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.360161Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.360161Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:998f6c1c6be2fd396d94e772f5f10cb3847ced03a546dd6ccee7627120becc3b","observation_id":"ff7200d3-2c76-4697-8469-64a11aa6b630","resolution":{"observed_at":"2026-08-11T00:46:41.360161Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.364766Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.364766Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:c40fb72c8852f09d2433f507b769d02a149ffa7b5e5a7ed4f17bebd67633208f","observation_id":"6531a895-7094-42b0-ab2e-7e66837fe665","resolution":{"observed_at":"2026-08-11T00:46:41.364766Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.370009Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.370009Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:2fe5f16736c309693ab0d929c12dcc67938df06764b9bed2d75a443d56259137","observation_id":"8b9382a4-d17d-4ca1-892f-168f181becd2","resolution":{"observed_at":"2026-08-11T00:46:41.370009Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.375018Z","title":"Lany and A","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.375018Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:7d6199d2ce77177531190b3f967a71ee94f1110c757a6f08a0f98d973f04f366","observation_id":"0813cfda-45cc-4e53-b5ca-7fd214bc6631","resolution":{"observed_at":"2026-08-11T00:46:41.375018Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.379976Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.379976Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:b713043b5d06c73d3ab4884ba891017a44a3b1a3ed25106ee7a6d6149468fe57","observation_id":"ee564699-2911-4068-be98-f97e79c5f89a","resolution":{"observed_at":"2026-08-11T00:46:41.379976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.384735Z","title":"Portoff, M","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.384735Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:39c9e92f653f8c1621e3f7c8a011ab56f7dc366adfb46fcde795be4c1f61298a","observation_id":"76e446ef-d9e0-4747-b83e-51815569ea57","resolution":{"observed_at":"2026-08-11T00:46:41.384735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:41.390683Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.390683Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:9c357b14a6060dcd153d7acc9c74cba37b015393aba54c2df21fb177dd8c420a","observation_id":"f8637b55-13e2-4a21-9087-598eda0f3432","resolution":{"observed_at":"2026-08-11T00:46:41.390683Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.337239Z","title":null,"venue":null,"work_id":"6500caae-06fd-4b47-a5f6-388edefc7685","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.395674Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:9f3dff10f306216b35775e0ae1374530a38b6f6220c4aa2132a9df161757b950","observation_id":"daa85166-557b-4297-9901-5ef4eb20094a","resolution":{"observed_at":"2026-08-11T00:46:43.342202Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.321011Z","title":"Lei and G","venue":null,"work_id":"0d709df1-e0e9-46c3-aca8-8de79d4ca292","year":2015},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.401835Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:173d98e9f8d4101e93c64f987c1c6c14cb2b7e6b5de252a5f84a71663a8c9e85","observation_id":"1314e988-6415-4e15-adab-45e15d977a37","resolution":{"observed_at":"2026-08-11T00:46:43.326424Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.300360Z","title":"Mazzolini, J","venue":null,"work_id":"ccac50f9-fc15-44bd-8005-e608c63828eb","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.406930Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:9adaa927f18edf7817e554172ac8dfee1ee1874a7dd1078b0f5001b8e09b6222","observation_id":"edb6c7d3-7ce5-4b08-9f8b-3b5bbeaec29e","resolution":{"observed_at":"2026-08-11T00:46:43.305752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.285223Z","title":"Okumura and J","venue":null,"work_id":"ed51a373-a1b6-408e-b1ab-d9281a37cafc","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.412567Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:f9b9daaf9d327cf89c2ba8b7f5d044842e06f51cea498471cf459cf142e412f4","observation_id":"c985dd21-bb8f-480e-a694-5e97bba7b41a","resolution":{"observed_at":"2026-08-11T00:46:43.289836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.269929Z","title":null,"venue":null,"work_id":"49764082-dd55-4cd3-8b10-64578e2806a0","year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.417417Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:62e1e48dcdf85893e3e38e3eccaf487762760d09dfde800e22fde9883449e3c6","observation_id":"3ade98c9-3778-4d31-8bf9-9d60d423b7e5","resolution":{"observed_at":"2026-08-11T00:46:43.274550Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.254629Z","title":"Karjalainen, V","venue":null,"work_id":"384cf86e-69d5-4494-8e80-ef93836a5e3f","year":2020},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.422268Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:fb75cf656244ea1fca509d308d14cc8dcc46987511915ebcb2eed687c1a10296","observation_id":"5ff6bedd-258a-4bba-ab76-a6932a9a1045","resolution":{"observed_at":"2026-08-11T00:46:43.259827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.238452Z","title":"Karjalainen, I","venue":null,"work_id":"c2e0d5e2-ac6d-41f1-a26b-01a684d23a62","year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.426989Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:8b5e8355559beefae2f7becb3a54edeb90da054af346f81e089b686708693320","observation_id":"fb086c52-0f13-4bdd-aea0-a00e9c6a90b8","resolution":{"observed_at":"2026-08-11T00:46:43.243485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.223691Z","title":"Skachkov, W","venue":null,"work_id":"fbf2d331-e911-4a4a-96ee-64e84cbe11a5","year":2019},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.431565Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:2865952998b0c2766d011284806311d77baddae4ce4142537f8617fc51b35b66","observation_id":"de53b5aa-45ae-433a-902d-779929cb9be7","resolution":{"observed_at":"2026-08-11T00:46:43.228299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.208796Z","title":null,"venue":null,"work_id":"f673cb60-653e-4060-b19e-9677f1ba0498","year":2019},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.437063Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:a73532dde4ff9ef3ef4b73b168ac2a00e6d26858446d6f45a2b3736cb2211fba","observation_id":"c432060e-fa02-4c87-a9df-e1779c6638c3","resolution":{"observed_at":"2026-08-11T00:46:43.213364Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.192425Z","title":null,"venue":null,"work_id":"05ddc343-fa99-4051-86df-0d2e14671002","year":2019},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.441695Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:08fe02da47ddc5191bef100c7b4873d0a1260fb8de4678d3e89ff51e32e5f173","observation_id":"54a8474f-b8b3-4ed9-9067-9c09f51b5efe","resolution":{"observed_at":"2026-08-11T00:46:43.197811Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.177275Z","title":null,"venue":null,"work_id":"bf392655-0a9e-4a2d-8326-cb5e5fc50b8f","year":2019},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.446821Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:243a7ec9791f59525323bb276a384d18b909bd15b1bc14ddc72f81bc786261fb","observation_id":"893b7b61-e63c-4b0f-954c-6b4f8a21b09f","resolution":{"observed_at":"2026-08-11T00:46:43.182163Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.161535Z","title":"Stavola, W","venue":null,"work_id":"959020c9-8506-4ee2-8627-4e33fd3bc298","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.451615Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:66f16739a515d5a7c6955821e00fa39d5c03324b0f8a85dac13a5ef6d07d35d9","observation_id":"452d2394-69f8-4e68-965a-8f8e37bb5edf","resolution":{"observed_at":"2026-08-11T00:46:43.167261Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.146052Z","title":"Weiser, M","venue":null,"work_id":"c5ad07b4-7fda-4fed-aaeb-4c31c1761b83","year":2018},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.456686Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:1e1438742c2f78053fa59f348741f7575471da1619f5ad8a40d685c8d90dfc9a","observation_id":"63110904-0c6a-4158-876f-4cc82c21b573","resolution":{"observed_at":"2026-08-11T00:46:43.150902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.128138Z","title":"Mosquera-Lois, S","venue":null,"work_id":"4f72dd46-ba0f-487a-a3a6-54e28d00501c","year":2022},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.461920Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:788cc3e2ad3e153973199b01f8bcd65231d8919ebd35a13868a7466848fcae64","observation_id":"aa0bb836-c09c-4b41-898a-760a8ae97f10","resolution":{"observed_at":"2026-08-11T00:46:43.134745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.112465Z","title":"Huang, Z","venue":null,"work_id":"02835a32-31ae-40f8-8e0b-58cd67a6cd16","year":2022},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.466794Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:0a3fbbd14da600577dea80637607f3bc5c2cd47991c9fc04654d168056d3986b","observation_id":"54b2be7a-5f19-4916-8aa0-639d098e2cd9","resolution":{"observed_at":"2026-08-11T00:46:43.117537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.095724Z","title":null,"venue":null,"work_id":"8812e08e-785d-4e18-a64c-514f66f35676","year":2008},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.471137Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:5f533ae4322629d40bfab6fad416a65362632db102867ecfaa28c95bbe0443bb","observation_id":"ddd44784-898d-49bd-a040-4a61630321af","resolution":{"observed_at":"2026-08-11T00:46:43.102057Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.079293Z","title":"Arrigoni and G","venue":null,"work_id":"c8f3cc65-6022-4abb-a5b8-e20c4fac5b9c","year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.477083Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:8388d76c8a3fac5dce36b65419df9660c2af0fbef23ee843e8676ff4d5315751","observation_id":"ffb6dc26-c51f-4088-8083-b584f82246f4","resolution":{"observed_at":"2026-08-11T00:46:43.084383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.059621Z","title":"Kumagai, N","venue":null,"work_id":"fc1d1056-ff06-4aa6-98d5-c4816f3c82e2","year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.482259Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:54bb0f1602e85a20acf67b966d1806e0f073ca9ad5eca060f48dc651f442f5b8","observation_id":"384a4658-f4f7-478b-a38c-b0ba556776c2","resolution":{"observed_at":"2026-08-11T00:46:43.065365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.042687Z","title":null,"venue":null,"work_id":"286e5481-2a91-4d64-bd41-d5ab03dde178","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.487285Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:da109103ad7c5e48048bd3b610c3ba2b2fcf3109c07eedec26e794c3a2225d7a","observation_id":"9839328d-3ffc-4a0a-a049-eff859876b4a","resolution":{"observed_at":"2026-08-11T00:46:43.047669Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.023091Z","title":null,"venue":null,"work_id":"32e39fad-c65e-41f9-bc0a-8cb0ff6b6840","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.492234Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:52ad4d25761f1638184aee21e1ef061e8c35ae19d7b605a1d4595bb33abf0740","observation_id":"502ac75a-3cd6-4159-9e2c-84395c92d584","resolution":{"observed_at":"2026-08-11T00:46:43.029281Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:43.000839Z","title":"Kresse and J","venue":null,"work_id":"4ee51b8b-f088-4cb3-a1ad-dae5cd814ac0","year":1993},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.496834Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:ba57282c23d9c2f18fee76294a0fb7f1a44fbaa94866a1e474c7fdb961941506","observation_id":"147e55b0-1404-460f-9d96-8c7d50342c2e","resolution":{"observed_at":"2026-08-11T00:46:43.007041Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.984633Z","title":"Kresse and J","venue":null,"work_id":"cfc2d1fa-e503-4b8f-a6ac-289981480ed0","year":1996},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.502378Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:66781a6c28215cf4a59a5a6e0638aec934e53b6332757c5677fe80272a1d8d31","observation_id":"0accf838-37ee-434f-90bb-554aeaa6e5eb","resolution":{"observed_at":"2026-08-11T00:46:42.989839Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.967980Z","title":"Kresse and J","venue":null,"work_id":"3541127d-a175-4814-81bf-b3eac96eb87d","year":1996},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.507486Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:40f5d0f742e9f23d73ece9d3ce70ababec2826f63dfe5c358d780ae2f44d3f05","observation_id":"14514333-fc01-49ac-ab66-a967f1210fd8","resolution":{"observed_at":"2026-08-11T00:46:42.973075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.951134Z","title":"Kresse and J","venue":null,"work_id":"cebd6bbd-3065-4744-96b5-8b2a1ba0c8a5","year":1994},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.511967Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:452426b16e2678dd37ad16f672ec59d4ce9735bde7574aedd3d262b401b8088d","observation_id":"9420953e-e6be-423d-81b7-f586dc8a9a33","resolution":{"observed_at":"2026-08-11T00:46:42.955884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.935635Z","title":"Kresse and D","venue":null,"work_id":"dbaf43d9-bcf8-494d-8b18-41428e27a779","year":1999},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.516620Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:4ad4a1fb41bff3f736966d2e5d32f7074302902db621d14302875be6936d2c2a","observation_id":"1132526e-0e90-4413-9596-49f66ad7809f","resolution":{"observed_at":"2026-08-11T00:46:42.940464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.918739Z","title":"Gajdoˇ s, K","venue":null,"work_id":"e5796394-0487-4dbf-a566-c4c1267f4137","year":2006},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.521439Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:eb366ee009c82ed564636fb9f73245caaf570095264746bb05e099faad1fdb5a","observation_id":"c5623068-9620-4f0e-baf5-9469c66afdc1","resolution":{"observed_at":"2026-08-11T00:46:42.923987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.902644Z","title":null,"venue":null,"work_id":"dada494c-2ea7-4b02-b418-b6a3480f2e62","year":1994},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.526452Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:5141a0d5b817b51318b85e08e81d696c012b3e573209d24fd91071bb45aadb11","observation_id":"1effc842-8299-45e8-8a79-30638d709771","resolution":{"observed_at":"2026-08-11T00:46:42.907554Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.885373Z","title":"Adamo and V","venue":null,"work_id":"4b7c37a7-fd03-4b92-9fb3-af7215a09036","year":1999},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.530875Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:4242e3f5386377bfca3b87373355098db2bcbbfa440ccd1d557cdf06e1c3a699","observation_id":"0d2300bb-1e34-44d6-9d80-c8c8e37878d8","resolution":{"observed_at":"2026-08-11T00:46:42.890444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.868794Z","title":null,"venue":null,"work_id":"8b81d643-109b-4bb9-8bee-048ab0ed4ce9","year":2008},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.536470Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:3d192f926ca3c4e0cb836a1a11a58aa307952d4d2f854c002752a55a2f473961","observation_id":"6d1c1b4a-0be5-4f3e-986e-48fdb979de9b","resolution":{"observed_at":"2026-08-11T00:46:42.874571Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.847739Z","title":null,"venue":null,"work_id":"4e4a64b3-96c3-4518-a3a8-0dd87559d281","year":2013},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.541189Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:cb0d5674168f8b090d7c69706a640d31cae495fcbc223e54af675659f6be290c","observation_id":"61f800d4-4405-4e91-9628-792fedc45c06","resolution":{"observed_at":"2026-08-11T00:46:42.854857Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.827160Z","title":null,"venue":null,"work_id":"b008171f-58b1-46d0-ad8f-658422457058","year":1996},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.546225Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:0a0eced269c3e81db618794f10327c9d3da2974ea0fb391595433655d0b35181","observation_id":"3af8b417-0e18-4f4b-a068-20363df5f091","resolution":{"observed_at":"2026-08-11T00:46:42.833686Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.810663Z","title":null,"venue":null,"work_id":"35114475-60d3-4b2e-8453-0f6d559499db","year":2013},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.550969Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:cc987ce974ad0f2f99ba72e4746a812ebecdd4fd81ad0b4f8002f00febe5df83","observation_id":"e7d35bef-7974-4120-b62d-ce7b09a3da14","resolution":{"observed_at":"2026-08-11T00:46:42.815552Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.00096","last_updated":"2025-09-04T13:50:21Z","snapshot_observed_at":"2026-08-04T22:35:15.439821Z","submitted_at":"2023-12-29T23:08:59Z","title":"A foundation model for atomistic materials chemistry","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.00096","snapshot_observed_at":"2026-08-11T00:46:41.555646Z","title":"Batatia, P","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.555646Z"},"links":{"cited_paper":"/paper/2401.00096","citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:f39c7cd8c04e8bd2408799189fee5b5432c77c0749f1266716ab897b064ab5e6","observation_id":"dd57b7cd-cdba-4578-8463-e0afe65e8bdd","resolution":{"observed_at":"2026-08-11T00:46:41.555646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.795005Z","title":"Batzner, A","venue":null,"work_id":"0fd6b451-7acf-4de5-ab70-207525550e5c","year":2022},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.560626Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:dc5c5617423c5384e332763e013fc7dea9ef35abc170991b46e5864006a4dd94","observation_id":"977b0694-2598-46f5-b6c7-1a1534299e29","resolution":{"observed_at":"2026-08-11T00:46:42.800107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.16068","last_updated":"2025-04-22T17:47:01Z","snapshot_observed_at":"2026-08-16T11:08:55.568282Z","submitted_at":"2025-04-22T17:47:01Z","title":"High-performance training and inference for deep equivariant interatomic potentials","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.16068","snapshot_observed_at":"2026-08-11T00:46:41.565818Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.565818Z"},"links":{"cited_paper":"/paper/2504.16068","citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:e1932d8e34d0a780e83a13cda96f260f798bb7c2319f715ec1e63e0d00cb2d17","observation_id":"169e44ba-e5e9-4555-ba12-af356f5ee05f","resolution":{"observed_at":"2026-08-11T00:46:41.565818Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.777699Z","title":null,"venue":null,"work_id":"5f7a95f7-c6ac-4e58-ad89-7688287a4b57","year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.570906Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:0231bf47f4d25135695c29da567fbb45ceba1bfe0b7d4221ea0b306162da0f1c","observation_id":"fe8e56ff-7a3f-487e-9e86-c10ada86d3ac","resolution":{"observed_at":"2026-08-11T00:46:42.783361Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.760606Z","title":"Mosquera-Lois, S","venue":null,"work_id":"3405b5a2-d85d-4f62-8428-ff12c094684e","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.575690Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:d9af7bf34deff0d03baac4356c226b350088081aeebb74113a2c51fdca63e7f9","observation_id":"55af808a-885b-4136-9a5a-3dc2d75f62ce","resolution":{"observed_at":"2026-08-11T00:46:42.766343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.741382Z","title":"Lany and A","venue":null,"work_id":"c58eeb07-df39-4f0b-8151-b2ddf9f264a8","year":2005},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.580896Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:902561c79859575b68070eacae58ddd8b127b9db99f147e654d9b19b6aeb2f4a","observation_id":"403c63df-3e82-44e8-aac4-72245e2e31e0","resolution":{"observed_at":"2026-08-11T00:46:42.747088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.723973Z","title":null,"venue":null,"work_id":"b6a3413e-3c01-4462-a551-4bc36fb283b3","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.585919Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:c6c94e606a255f8d98fd4e39f19d565384eceb699438645f5eccfd2eb0fcbc0c","observation_id":"2e39884a-33bb-4458-9b4e-79a718f8c77b","resolution":{"observed_at":"2026-08-11T00:46:42.729495Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.705541Z","title":null,"venue":null,"work_id":"5a11acf0-1d85-4c08-a594-8e3f3022b9a0","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.591081Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:7e17cb916e82ad791713b58b2ab4abfd875d67942da5e039f2bc893e567f02b8","observation_id":"42ad75a3-9454-4a33-9b3a-1dfa9264240b","resolution":{"observed_at":"2026-08-11T00:46:42.710464Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.685394Z","title":"Nicolson, S","venue":null,"work_id":"aa3d2afc-276a-4aff-95a4-992a50462c9f","year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.597575Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:ca0e944f7decc3c45175c1e0c8627e1e9d008fe9af4d20f42bcb05cc69301c54","observation_id":"16b0c946-dca8-4ce7-9f7e-27f514f1c5e4","resolution":{"observed_at":"2026-08-11T00:46:42.693611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.662403Z","title":null,"venue":null,"work_id":"728c712b-2dd6-403e-b1ae-56dad6b1ebcd","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.603090Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:33c07f09d860807ed72746c9317099b23f18446a24a0908993ec680837b102f0","observation_id":"8c2d98fa-5ef2-44cc-9302-de22ca7d730e","resolution":{"observed_at":"2026-08-11T00:46:42.669299Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.635488Z","title":null,"venue":null,"work_id":"42c5c7e6-4792-4c89-a6c3-3741aca74a34","year":1996},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.607819Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:6022de85a9f99b563629b807e354fad54f2cfad51290aace719f12badff8b8a0","observation_id":"7bb8684e-7695-49ff-98bb-e85b38b89d0d","resolution":{"observed_at":"2026-08-11T00:46:42.642812Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.617172Z","title":"Zhang, H","venue":null,"work_id":"184bc2ef-3509-4ca2-98a9-bec13bf0854f","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.612792Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:ef1719a0bf745698ba21a781ca3a5a894c90b316d803ca6c70524ab08019e4b0","observation_id":"be5b1169-28f5-4fb0-92b4-f8a9e6cc988c","resolution":{"observed_at":"2026-08-11T00:46:42.622575Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.596204Z","title":"Yuan and G","venue":null,"work_id":"954a0601-3baa-4e6e-9e15-5cf97145fef6","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.618003Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:fff61d9835fe53b351fbf0e2d16f9e696dc589b49079ca9bfdedd86a967160f4","observation_id":"ec93a325-7e98-4580-9d1f-784fd48808f1","resolution":{"observed_at":"2026-08-11T00:46:42.605099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.577080Z","title":null,"venue":null,"work_id":"b8beff21-fa61-48ff-b375-783d95c46e34","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.622938Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:2dd947e2b19ee625398f3bb6ccd6bb57587310338f0f1a95b0791f903ae4d77e","observation_id":"be85e29c-db07-4917-b42d-af51aa00d30d","resolution":{"observed_at":"2026-08-11T00:46:42.583653Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.557658Z","title":"Hoang and M","venue":null,"work_id":"77169b3f-99f4-4356-99f5-651ad12d8cf2","year":2014},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.628260Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:c0c1b6116dff71dda35108a7ee85a9ad61b521bcf77f618c1d390347fb19c57b","observation_id":"46391319-cae3-4b26-a7a6-adae12ee861e","resolution":{"observed_at":"2026-08-11T00:46:42.563811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.540935Z","title":null,"venue":null,"work_id":"788bef94-9b50-40bb-932d-253e7856c2a1","year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.632934Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:21fb4589145b2b3415d2732a284d07209c3f6a9085df759973a8c4aae9122e80","observation_id":"6364de79-9dfc-4f81-a10b-15860b065ceb","resolution":{"observed_at":"2026-08-11T00:46:42.546469Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.521978Z","title":null,"venue":null,"work_id":"cf626369-075b-44c1-81c5-cb6227881977","year":2020},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.637848Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:72cab4d55bafe8bddf2296111c305497c9ffe850ce23d80c1c5a2a57c5071493","observation_id":"16c52742-0bb8-4342-b1c9-6457c4fd5f06","resolution":{"observed_at":"2026-08-11T00:46:42.527737Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.505073Z","title":"Zhang, L","venue":null,"work_id":"073f8520-a83a-4e74-8577-f444240345ae","year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.643663Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:7cc27c7cd43e0a707f1016b366c718cc55a5b70ede00a5c2bd8bd3849d8070c6","observation_id":"47ca6c74-7d87-4c9d-9a9d-39f7eee3d9cd","resolution":{"observed_at":"2026-08-11T00:46:42.510109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.486302Z","title":"Grasser, B","venue":null,"work_id":"a112b94a-d5ae-48ac-8a03-a0625bc9e403","year":2009},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.648531Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:64c75672ae57f2a272740b10a726d63972d662728659c21116662c998e19a09c","observation_id":"fa8766fe-dd8c-4b47-9c5f-fce9b96fc5d6","resolution":{"observed_at":"2026-08-11T00:46:42.491477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.468070Z","title":null,"venue":null,"work_id":"71b407ac-69fc-46d1-ae62-775432956beb","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.653407Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:5b564d3e2ed5105ce87e8fe968da744096886a9f7a946c638dc4b2bde4df76a6","observation_id":"aee38291-33ea-4ffc-82b6-99c9aab927da","resolution":{"observed_at":"2026-08-11T00:46:42.474031Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.452654Z","title":"Kuganathan, P","venue":null,"work_id":"f6b3d211-7b2d-4ef7-a78a-400649c7f990","year":2019},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.658019Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:2e2717d7b7beaa2d28734dff5f608f8ef9e0c04acc62e5994300fbd678c3d612","observation_id":"8fbc5eb5-abfd-4012-8825-1868b376074f","resolution":{"observed_at":"2026-08-11T00:46:42.457463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.436487Z","title":null,"venue":null,"work_id":"5f1516ca-7643-49dd-b2f8-94c1a3b89938","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.662710Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:979d4fa43e41ebc1063751e2b0701f6d9c198c0cd8200f27039aa02fad454bd5","observation_id":"d0fbf25d-e004-41c2-a150-2b7698a0f9d6","resolution":{"observed_at":"2026-08-11T00:46:42.441626Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.419667Z","title":null,"venue":null,"work_id":"65d29523-72ec-4374-97de-d299a03e370a","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.668255Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:8a8c9c68036002a4bb74d85bc0d996652e6965c22c9fc606fa2cc850475c848b","observation_id":"306501b4-50fd-4b2e-9c42-a7a66decb50e","resolution":{"observed_at":"2026-08-11T00:46:42.424786Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.402836Z","title":"Sathasivam, B","venue":null,"work_id":"c9c11a56-85a9-4f89-948f-e0176a0c9439","year":2017},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.673976Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:2107983c57ccd9c4d88720ebec5aeb5b03086d1212924fa450a3d4fbbfafea7e","observation_id":"9cbbc731-bee7-472b-961f-823e65d63c23","resolution":{"observed_at":"2026-08-11T00:46:42.407762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.386272Z","title":"Han and T","venue":null,"work_id":"df3e7691-8dfa-406a-ae13-e542211af61d","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.679775Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:7d2a73b6169128cb32923cc546579c6891e7b58071a7a52ad167297eaff943ac","observation_id":"44f4eda8-632b-41c3-8445-9a9e04555daf","resolution":{"observed_at":"2026-08-11T00:46:42.391867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.369898Z","title":null,"venue":null,"work_id":"765cba4c-4a72-47e3-8902-c5f8c2f63dbc","year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.685032Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:42178fbdf734a6114395bc083bfc4c448de380fa17cccda8c1b4664fe4c8f192","observation_id":"4f75a019-5a20-4fb7-9569-8b96623c05a8","resolution":{"observed_at":"2026-08-11T00:46:42.375225Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.351118Z","title":"Banerjee, E","venue":null,"work_id":"031e99cc-03cf-4e60-9924-900b8b72bf71","year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.690538Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:0a238987b63843bb008ec8b144cff755e1d5d0b456a7fc220c6d371a751ec666","observation_id":"cb25cf61-2008-4129-80cf-976346020ce3","resolution":{"observed_at":"2026-08-11T00:46:42.357093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.331500Z","title":null,"venue":null,"work_id":"5236e66f-49d9-4afe-a1c2-5c7495c29aad","year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.695596Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:3bb1d3e37e005efe69f0f7afe83e7bdf67ef3b922fb95587e55cafaae2f3dcab","observation_id":"79fc680f-0bc9-4395-a852-cdd92c335438","resolution":{"observed_at":"2026-08-11T00:46:42.336966Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.310381Z","title":"Sucharitakul, G","venue":null,"work_id":"b47a7260-f7ba-489f-933f-26df0a5da27c","year":2017},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.700333Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:e6e475d831acbd95a730d183bdcf3dbf9f924cbdc1f6efe3b38c889abdc11ef1","observation_id":"af3f2989-056e-45ba-9dbe-1d0a31d1b003","resolution":{"observed_at":"2026-08-11T00:46:42.319851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.293192Z","title":"Vinckeviˇ ci¯ ut˙ e, M","venue":null,"work_id":"7ff7e0ba-b92f-4a31-8454-92db4f59759e","year":2019},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.705493Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:e503d977575761cd5258f323b10a8342867fd8f6804ac16dd806c741855ec552","observation_id":"8a8cc134-8144-4e5a-b69d-8206c4c0e5b4","resolution":{"observed_at":"2026-08-11T00:46:42.298672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.274430Z","title":null,"venue":null,"work_id":"ff561c8a-7610-4bdf-bf4b-6b05dfdd84f7","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.710206Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:9c67972266c2b13ca17650b1a0df77dc985cc56f32848d62189671ea2de64317","observation_id":"8e1f8a01-1172-4a6c-897a-95d2af3de8de","resolution":{"observed_at":"2026-08-11T00:46:42.280883Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.14920","last_updated":"2024-12-10T23:52:04Z","snapshot_observed_at":"2026-08-16T15:05:06.714860Z","submitted_at":"2023-08-28T22:29:57Z","title":"Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.14920","snapshot_observed_at":"2026-08-11T00:46:41.714893Z","title":"Riebesell, R","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.714893Z"},"links":{"cited_paper":"/paper/2308.14920","citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:552caeed2e31563ecd7787c800357d1c7f0468d24efc084addf5856e2a5b4dcc","observation_id":"45485ef0-4e79-4f97-bc6a-335374fdf509","resolution":{"observed_at":"2026-08-11T00:46:41.714893Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.259190Z","title":null,"venue":null,"work_id":"0730f23c-b841-4740-ba4a-f73f7deace67","year":2023},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.722962Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:fb05be2cc1b35f8105f2cb3b6c6d85237505e0d66945a4e857ca7fb9181bce3c","observation_id":"c4d929e0-a47a-4fcc-ab70-71460fa90743","resolution":{"observed_at":"2026-08-11T00:46:42.264120Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.242327Z","title":"Batatia, D","venue":null,"work_id":"a80713ab-6dc7-4da5-8a52-4eb5c30ee14f","year":2022},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.730356Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:0ff6e4e28b7851a905e5f62183da08bbc7c135da774570fe8b960188dfe59879","observation_id":"8a4f298a-a712-4fbb-8958-04d0b730d0d1","resolution":{"observed_at":"2026-08-11T00:46:42.247771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.222850Z","title":null,"venue":null,"work_id":"f01e3730-1a57-4753-8766-d909ed9ff3eb","year":null},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.738245Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:ed4daf9634efa1ad812a7416507d7933e29d2db7f4be2f1aac6adac6970b5322","observation_id":"f5d4e8b0-ebc0-4416-b649-63c2a7335a10","resolution":{"observed_at":"2026-08-11T00:46:42.228847Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.207952Z","title":null,"venue":null,"work_id":"42e1b7f9-bad3-4d67-a305-66e107739350","year":2017},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.743675Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:db8ebc831c8ef39c54fa441abd3f5488cd19b61d86519aca0659659b652c23e3","observation_id":"7eada120-ffe4-4002-b3ac-0ba20e5f86a2","resolution":{"observed_at":"2026-08-11T00:46:42.212716Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.192349Z","title":"Batatia, S","venue":null,"work_id":"e27c16b8-6e62-45fa-a664-bd65bc0d9183","year":2025},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.750549Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:2db6ea132865744401cab098234dd107d93501dc1000d5c0a7e25e35d7ae7b69","observation_id":"bae1ce8a-af93-436a-8942-0d9e042b6eb2","resolution":{"observed_at":"2026-08-11T00:46:42.197052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.176379Z","title":null,"venue":null,"work_id":"73879348-e439-4462-a346-5bb26fe67dc2","year":2025},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.756001Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:ef6511e483d8679f7193d90b8d946a234bc7656654ac6b976c91ebe79e4258da","observation_id":"428d04aa-27ec-4dbf-80e2-2a0809e9cfd3","resolution":{"observed_at":"2026-08-11T00:46:42.181319Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.159750Z","title":"Krasikov and I","venue":null,"work_id":"97dcbe98-ea4a-4da5-a3c4-54c2751b564b","year":2017},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.763450Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:244e1c7fe0cd87459cb33f2d9b5afd1c0627af9c93117b9b9b72fd3fb6e28c7b","observation_id":"7aabb96c-1d00-4f2e-b224-a8a5abfc6dd4","resolution":{"observed_at":"2026-08-11T00:46:42.164580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.137454Z","title":"Razinkovas, M","venue":null,"work_id":"f32c3349-7262-46e7-a918-fa3da6cbf0f9","year":2021},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.770179Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:a735bc05f95469774b1fb9fce6269aaa7d5bfb31716239539040e5fac537f24b","observation_id":"6bee359c-87c0-4829-bca4-2879314f153f","resolution":{"observed_at":"2026-08-11T00:46:42.145854Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.107007Z","title":"Xiong, J","venue":null,"work_id":"dde849a7-03a5-4155-93c7-d9c394c2f9fb","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.775431Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:6fb93d6b28cc16e83cba0f718df715e693a05288401b2ac64ca5f914ccd0ddb1","observation_id":"f3ee5f18-158a-4e35-8613-3f0d3c8815d3","resolution":{"observed_at":"2026-08-11T00:46:42.113166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.087588Z","title":"Davidsson, W","venue":null,"work_id":"c57571ce-fb29-4698-83f4-ef7fa8975a21","year":2024},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.780928Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:222014c8b1f576c47e52be61acc556001393945df4ebf1809c85f11d1fcf6a6e","observation_id":"a3a0bc68-0d54-454b-9807-af1ab641c775","resolution":{"observed_at":"2026-08-11T00:46:42.093542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T00:46:42.068455Z","title":"O’Keefe and N","venue":null,"work_id":"4d3c1b02-ed40-412c-8a64-f11dc9d31d03","year":1991},"citing_paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics","version":3},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-11T00:46:41.787955Z"},"links":{"citing_paper":"/paper/2412.19330"},"observation_digest":"sha256:961c6e185f5e88a787951b6171ca33504f9deecabbf960954ca4c6bcd9f256e3","observation_id":"22d8c156-34f0-414d-bc61-a509f3e1ee17","resolution":{"observed_at":"2026-08-11T00:46:42.075115Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.19330","last_updated":"2025-05-08T18:51:18Z","latest_version":3,"primary_category":"cond-mat.mtrl-sci","snapshot_observed_at":"2026-08-12T14:44:14.932799Z","submitted_at":"2024-12-26T18:58:52Z","title":"Identifying Split Vacancy Defects with Machine-Learned Foundation Models and Electrostatics"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":58,"verified_exact":1,"verified_fuzzy":41},"total_outbound_references":104},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 100 of 104 outbound references and 3 inbound Pith citation observations for arXiv:2412.19330."}